A new hybrid matheuristic optimization algorithm for solving design and network engineering problems

Chagwiza, Godfrey; Jones, Brian Christopher; Hove-Musekwa, Senelani D.; Mtisi, Sobona

doi:10.1080/17509653.2016.1269136

Cited by 4 publications

(3 citation statements)

References 39 publications

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“…Moreover, the hybrid algorithm is formulated by combining Grotschel–Holland and max–min ant system algorithms to solve the network problem. The results show that the hybrid algorithm is very efficient (Chagwiza et al , 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

Application of variable neighborhood search for solving large-scale many to many hub location routing problems

Abbasi

Mokhtari

Shahvar

et al. 2019

JAMR

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Purpose The purpose of this paper is to solve large-scale many-to-many hub location-routing problem (MMHLRP) using variable neighborhood search (VNS). The MMHLRP is a combination of a single allocation hub location and traveling salesman problems that are known as one of the new fields in routing problems. MMHLRP is considered NP-hard since the two sub-problems are NP-hard. To date, only the Benders decomposition (BD) algorithm and the variable neighborhood particle swarm optimization (VNPSO) algorithm have been applied to solve the MMHLRP model with ten nodes and more (up to 300 nodes), respectively. In this research, the VNS method is suggested to solve large-scale MMHLRP (up to 1,000 nodes). Design/methodology/approach Generated MMHLRP sample tests in the previous work were considered and were added to them. In total, 35 sample tests of MMHLRP models between 10 and 1,000 nodes were applied. Three methods (BD, VNPSO and VNS algorithms) were run by a computer to solve the generated sample tests of MMHLRP. The maximum available time for solving the sample tests was 6 h. Accuracy (value of objective function solution) and speed (CPU time consumption) were considered as two major criteria for comparing the mentioned methods. Findings Based on the results, the VNS algorithm was more efficient than VNPSO for solving the MMHLRP sample tests with 10–440 nodes. It had many similarities with the exact BD algorithm with ten nodes. In large-scale MMHLRP (sample tests with more than 440 nodes (up to 1,000 nodes)), the previously suggested methods were disabled to solve the problem and the VNS was the only method for solving samples after 6 h. Originality/value The computational results indicated that the VNS algorithm has a notable efficiency in comparison to the rival algorithm (VNPSO) in order to solve large-scale MMHLRP. According to the computational results, in the situation that the problems were solved for 6 h using both VNS and VNPSO, VNS solved the problems with more accuracy and speed. Additionally, VNS can only solve large-scale MMHLRPs with more than 440 nodes (up to 1,000 nodes) during 6 h.

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Section: Literature Reviewmentioning

confidence: 99%

Application of variable neighborhood search for solving large-scale many to many hub location routing problems

Abbasi

Mokhtari

Shahvar

et al. 2019

JAMR

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“…flocking. PSO is widely used because of its robustness, global convergence capability, and easy implementation (Xie, Wang, & Li, 2012;Chagwiza, Jones, Hove-Musekwa, & Mtisi, 2018).…”

Section: Pso Algorithmmentioning

confidence: 99%

Damage Detection for Uhpfrc Communication Tower Based on Frequency Data and Particle Swarm Optimization

Jabbar

Hejazi

Hanoon

et al. 2019

Journal of Civil Engineering and Management

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Advances in the telecommunication and broadcasting sectors have increased the need for networking equipment of communication towers. Slender structures, such as towers, are sensitive to dynamic loads, such as vibration forces. Therefore, the stability and reliability performance of towers can be maintained effectively through the prompt detection, localization, and quantification of structural damages by obtaining the dynamic frequency response of towers. However, frequency analysis for damaged structures requires long computational procedures and is difficult to perform because of the damages in real structures, particularly in towers. Therefore, this study proposed a correlation factor that can identify the relationship between frequenciesunderhealthy and damaged conditions of ultra high performance fiber-reinforced concrete (UHPFRC) communication towers using particle swarm optimization. The finite element method was implemented to simulate three UHPFRC communication towers, and an experimental test was conducted to validate and verify the developed correlation factor

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“…Hence, there is space for research and experiments for enhancing the performance of SOS in exploiting and exploring the discrete solutions. Choosing a useful hybrid approach is a key determinant for achieving the best performance in solving a difficult problem [22,23].…”

Section: Introductionmentioning

confidence: 99%

A Novel Hybrid Metaheuristic Algorithm for Optimization of Construction Management Site Layout Planning

Prayogo

Cheng

et al. 2020

Algorithms

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Symbiotic organisms search (SOS) is a promising metaheuristic algorithm that has been studied recently by numerous researchers due to its capability to solve various hard and complex optimization problems. SOS is a powerful optimization technique that mimics the simulation of the typical symbiotic interactions among organisms in an ecosystem. This study presents a new SOS-based hybrid algorithm for solving the challenging construction site layout planning (CSLP) discrete problems. A new algorithm called the hybrid symbiotic organisms search with local operators (HSOS-LO) represents a combination of the canonical SOS and several local search mechanisms aimed at increasing the searching capability in discrete-based solution space. In this study, three CSLP problems that consist of single and multi-floor facility layout problems are tested, and the obtained results were compared with other widely used metaheuristic algorithms. The results indicate the robust performance of the HSOS-LO algorithm in handling discrete-based CSLP problems.

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A new hybrid matheuristic optimization algorithm for solving design and network engineering problems

Cited by 4 publications

References 39 publications

Application of variable neighborhood search for solving large-scale many to many hub location routing problems

Application of variable neighborhood search for solving large-scale many to many hub location routing problems

Damage Detection for Uhpfrc Communication Tower Based on Frequency Data and Particle Swarm Optimization

A Novel Hybrid Metaheuristic Algorithm for Optimization of Construction Management Site Layout Planning

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